A theoretical basis to the automated detection of copying between texts, and its practical implementation in the Ferret plagiarism and collusion detector

The theoretical background to the automated detection of plagiarism and collusion is investigated in this paper. We examine the underlying concepts, and see how features of language can be exploited to produce an effective system. Independently written texts have markedly different characteristics to those that include passages that have been fully or partially copied, and they can be effectively identified. The paper describes the implementation of the Ferret plagiarism and collusion detector, and its use in the University of Hertfordshire and other institutions. The difference between human and machine analysis is examined, and we conclude that an approach using machine processing is likely to be necessary in many situations.